Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/resnet-18
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: resnet-18-resnet-18
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.3541666666666667
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# resnet-18-resnet-18
+
+This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 5878685290980833992550249398272.0000
+- Accuracy: 0.3542
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss                        | Epoch  | Step | Validation Loss                      | Accuracy |
+|:------------------------------------:|:------:|:----:|:------------------------------------:|:--------:|
+| No log                               | 0.8889 | 6    | 5256596847186447919144532705280.0000 | 0.3542   |
+| 6252348666680642391375611953152.0000 | 1.9259 | 13   | 5816409290772115792559022800896.0000 | 0.3542   |
+| 5941338476045271956843984322560.0000 | 2.9630 | 20   | 5569209952566045840858865991680.0000 | 0.3542   |
+| 5941338476045271956843984322560.0000 | 4.0    | 27   | 5764530657074993210784856670208.0000 | 0.3542   |
+| 5978113032337293509815187800064.0000 | 4.8889 | 33   | 5717174614869048956753266343936.0000 | 0.3542   |
+| 6377920275134342219963975073792.0000 | 5.9259 | 40   | 5885479454087068208512098107392.0000 | 0.3542   |
+| 6377920275134342219963975073792.0000 | 6.9630 | 47   | 5693683372805207289944963284992.0000 | 0.3542   |
+| 6201930657158778429750307192832.0000 | 8.0    | 54   | 5815479022353922335409086398464.0000 | 0.3542   |
+| 6266525497982100125501481811968.0000 | 8.8889 | 60   | 5878685290980833992550249398272.0000 | 0.3542   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

model.safetensors

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